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Record W2806004154 · doi:10.1177/2054358118778564

Transfusion Management of Incident Dialysis Patients in Canada: A Prospective Observational Study

2018· article· en· W2806004154 on OpenAlexafffundabout
Aminu K. Bello, Christine Ribic, Serge Cournoyer, Mercedeh Kiaii, Martine Leblanc, Melanie Poulin-Costello, David Churchill, Norman Muirhead

Bibliographic record

VenueCanadian Journal of Kidney Health and Disease · 2018
Typearticle
Languageen
FieldMedicine
TopicErythropoietin and Anemia Treatment
Canadian institutionsWestern UniversityAmgen (Canada)University of British ColumbiaUniversité de SherbrookeMcMaster UniversityUniversité de MontréalUniversity of Alberta
FundersAmgen CanadaAstellas PharmaCanadian Society of NephrologyAmgen
KeywordsMedicineObservational studyBlood transfusionHemodialysisAnemiaDialysisProspective cohort studyPeritoneal dialysisInternal medicinePediatricsSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Several studies have demonstrated harm associated with using erythropoiesis-stimulating agents (ESA) to achieve higher hemoglobin (Hb) levels. Subsequently, more conservative use of ESAs has changed anemia therapy in patients with chronic renal failure. OBJECTIVE: The objectives were to identify transfusion rates in hemodialysis (HD) patients during the first year of therapy, to identify factors associated with the probability of transfusion, describe reasons for the transfusions, and identify the Hb values associated with each transfusion. An exploratory objective was to describe the age of red blood cell transfusions. DESIGN: This was a multicenter prospective observational cohort study. SETTING: There were 12 study sites in 5 Canadian provinces. The study was performed from 2012 to 2014. METHODS: The study patients were adult incident chronic HD patients in these centers. Patients with acute kidney injury, peritoneal dialysis, and planned transfer to satellite units were excluded. Patients had to receive at least 1 month of chronic HD to be eligible. Data for 3 months prior to HD were obtained by retrospective chart review. Prospectively, charts were reviewed monthly for 12 months for data abstraction. RESULTS: There were 314 patients enrolled and 79.9% completed 12 month follow-up. Ninety-four (29.9%) patients received at least 1 unit of blood. During the first 90 days, the transfusion episode rate was 148.4 per 100 patient-years compared with 62.6 per 100 patient-years post 90 days. The most frequent indication was a low Hb value (92%) with gastrointestinal bleeding, surgical blood loss, and fatigue accounting for 9.9%, 8.6%, and 4.5%, respectively. Some patients had >1 indication. The mean Hb values prior to transfusion episodes ranged from 75.3 to 78.6 g/L. Cox regression analysis on time to first transfusion and time to first hospitalization/death both showed an association with inpatient initiation of HD. Some 37.5% initiated HD as an inpatient and differed from those starting as an outpatient. They had less predialysis care and laboratory data suggested more inflammation. The mean and median ages of the blood units transfused were 24.9 (SD = 10.0) and 23 days (interquartile range = 17-33). CONCLUSIONS: This work reported the blood transfusion rate in incident HD patients in Canada during a period associated with conservative ESA prescription. The major indication for transfusion was a low Hb rather than clinical symptoms. Initiation of HD as an inpatient was independently associated with the probability of receiving a blood transfusion. These findings require further investigation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.005
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.284
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2018
Admission routes3
Has abstractyes

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